Efforts to learn more about the oceans that surround us have increased dramatically as the technological ability to do so grows. Autonomous Underwater Vehicles (AUVs) are one such technological advance. They allow for rapid deployment and can gather data quickly in places and ways that traditional measurement systems (bouys, profilers, etc.) cannot. A ROMS-based data assimilation method was developed that intelligently plans for and integrates AUV measurements with the goal of minimizing model standard deviation. An algorithm developed for this system is first described that optimizes paths for AUVs that seeks to improve the model by gathering data in high-interest locations. This algorithm and its effect on the ocean model are tested by comparing the results of missions made with the algorithm and missions created by hand. The results of the experiments demonstrate that the system is successful in improving the ROMS ocean model. Also shown are results comparing optimized missions and unoptimized missions.

Conventional streamlined autonomous underwater vehicles (AUVs) with a single thruster and stern planes are typically trimmed to be somewhat buoyant or heavy in water. To maintain depth, they must generate a constant hydrodynamic force which requires that they swim at a constant pitch angle. Although tail fins are the typical mechanism for generating this control moment, they become ineffective at low speeds. To enable an existing AUV to travel at lower speeds, one may easily incorporate a modular moving mass actuator. In some cases, it may also be advantageous to include a fixed wing. The equations of motion and equilibrium conditions to regulate depth are derived, and the effectiveness and low-speed efficiency of a fixed wing is evaluated. The effect of the vertical offset of the moving mass is analyzed to establish the relation between the control angle and the moving mass linear position. A description of the design of a one degree of freedom moving mass actuator module and preliminary experiments using the Virginia Tech Miniature AUV is provided. Data is presented for a series of fixed MMA position experiments as well as a dynamic position test. The results illustrate the effectiveness of a moving mass actuator at generating low-speed control moments. With the collected data, parameter identification is performed to get an estimate of the hydrodynamic parameters. / Master of Science

Buoyancy driven underwater gliders, which locomote by modulating their buoyancy and their attitude with moving mass actuators and inflatable bladders, are proving their worth as efficient long-distance, long-duration ocean sampling platforms. Gliders have the capability to travel thousands of kilometers without a need to stop or recharge. There is a need for the development of methods for hydrodynamic modeling. This thesis aims to determine the hydrodynamic parameters for the governing equations of motion for three autonomous underwater vehicles. This approach is two fold, using data obtained from computational flight tests and using a semi-empirical approach. The three vehicles which this thesis focuses on are two gliders (Slocum and XRay/Liberdade), and a third vehicle, the Virginia Tech Miniature autonomous underwater vehicle. / Master of Science

The Virginia Tech Trawl-Resistant Self-Mooring Autonomous Underwater Vehicle (TRSMAUV) is designed to reside on the seafloor for extended periods of time. The TRSMAUV shape allows for deployment in areas where trawl fisheries are conducted. TRSMAUV is a two stage vehicle. The ingress vehicle is the delivery device, and it is constructed from two symmetric halves. The top half contains the ingress vehicle propulsion system and control surfaces. The bottom half is the trawl-resistant mooring package. A smaller vehicle, the egress vehicle, is housed within the bottom ingress half and provides the guidance, navigation and control algorithms for the TRSMAUV. This report covers the general design elements of the TRSMAUV, the detail design of several prototypes, the results of the field trials, and the next steps that will be taken to build the final vehicle. / Master of Science

The design method for marine propulsor (propeller/stator) is presented for an autonomous underwater vehicle (AUV) that operates at a very high loading condition. The design method is applied to Virginia Tech Dragon AUV. It is based on the parametric geometry definition for the propulsor, use of high-fidelity CFD RANSE solver with the transition model, construction of the surrogate model, and multi-objective genetic optimization algorithm. The CFD model is validated using the paint pattern visualization on the surface of the propeller for an open propeller at model scale. The CFD model is then applied to study hydrodynamics of ducted propellers such as forces and moments, tip leakage vortex, leading-edge flow separation, and counter-rotating vortices formed at the duct trailing edge. The effect of variation of thickness for stator blades and different approaches for modeling the postswirl stator is presented. The field trials for Dragon AUV shows that there is a good correlation between expected and achieved design speed under tow condition with the designed base propulsor. The marine propulsor design is further improved with an objective to maximize the propulsive efficiency and minimize the rolling of AUV. The stator is found to eliminate the swirl component of velocity present in the wake of the propeller to the maximum extent. The propulsor designed using this method (surrogate-based optimization) is demonstrated to have an improved torque balance characteristic with a slight improvement in efficiency than the base propulsor design. / Master of Science / The propulsion system is the critical design element for an AUV, especially if it is towing a large payload. The propulsor for towing AUVs has to provide a very large thrust and hence the propulsor is highly loaded. The propeller has to rotate at very high speed to produce the required thrust and is likely to cavitate at this high speed. Also at this high loading condition, the maximum ideal efficiency of the propulsor is very less. Another challenge is the induced torque from the propeller on AUV that can cause the rolling of an AUV which is undesirable. This problem can be addressed by installing the stator behind the propeller that will produce torque in the opposite direction of the propeller torque. In this work, we present a design methodology for marine propulsor (propeller/stator) that can be used in AUV towing a large payload. The propulsor designed using this method has improved torque characteristics and has the efficiency close to 80 % of the ideal efficiency of ducted propeller at that loading condition.

Miniature Autonomous Underwater Vehicles are a major area of research and development today. Because of their size and agility, they are capable of exploring and operating in smaller bodies of water in addition to areas of the ocean that would be out of reach for a larger vehicle. Being autonomous requires that the system must be capable of performing without the need for human supervision, so use of external sensors such as sonar are needed to ensure the safety of the vehicle during missions. However, since all of the onboard instrumentation and external equipment must also be miniature in size, the implementation of a small sonar system is desirable. This thesis contains a brief introduction to sound and sonar, leading into a description of the design and development of a small, inexpensive sonar altimeter. Piezoelectric material is used for transduction in the sonar system while a PIC microcontroller processes the return signals from the water. This altimeter was made to be implemented on a miniature autonomous underwater vehicle developed by the Autonomous Systems and Controls Laboratory at Virginia Polytechnic Institute. In addition to being capable of reporting ocean depths, sonar systems can be used to aid in the navigation of underwater vehicles. A constant altitude controller based on sonar data has been designed, tested, and implemented on the autonomous underwater vehicle. Possibilities for an obstacle avoidance system involving sonar are also discussed in this thesis. / Master of Science

SMaRC, Swedish Maritime Robotics Centre, arbetar med att utveckla morgondagens smarta undervattenssystem. Ett av dessa system är den autonoma undervattensroboten SAM. Autonoma undervattensfarkoster, förkortat AUV, spelar en nyckelroll inom bland annat forskning, försvar och havsindustrin. När AUVerna blir billigare och lättare att manövrera, blir även havet och livet under ytan mer tillgängligt för människor. Syftet med detta projekt var därför att utveckla en ny utformning på propellersystemet till SAM.  Första steg i projektet var att designa det nya propellersystemet i CAD-verktyget Solid Edge. Därefter blev de olika komponenterna 3D-printade och skruvades ihop. I den nya designen av propellersystemet ersattes den ursprungliga motorn till SAM med två färdigtillverkade motorer från Blue Robotics. Motorbytet medförde en ändring i SAMs tyngdpunkt, vilket gjorde det nödvändigt att undersöka krafterna som verkade på farkosten. För att återskapa SAMs stabilitet integrerades stålvikter i designen för att balansera motorernas nya placering. När en modell som uppfyllde designkraven var färdig, testades prototypen på land. På grund av tidsbrist hanns inte en testning i vatten genomföras.  Slutresultatet är en tredelad lösning som innefattar en axel, en framdel och en dysa. När projektet påbörjades hade propellersystemet en massa på cirka 1.34 kg i luft, varav det nya systemet har massan 1.185 kg med motvikterna i luft. Detta ger en minskning av massan på ungefär 22 procent. Vid ett senare skede kommer axeln att tillverkas i aluminium, vilket vill ge en viktminskning med ungefär 9 procent istället.

There are benefits to the use of internal actuators for rotational maneuvers of small-scale underwater vehicles. Internal actuators are protected from the outside environment by the external pressure hull and will not disturb the surrounding environment during inspection tasks. Additionally, internal actuators do not rely on the relative fluid motion to exert control moments, therefore they are useful at low speed and in hover. This paper describes the design, fabrication and testing of one such autonomously controlled, internally actuated underwater vehicle. The Internally Actuated, Modular Bodied, Untethered Submersible (IAMBUS) can be used to validate non-linear control strategies using internal actuators. Vehicle attitude control is provided by three orthogonally mounted reaction wheels. The housing is a spherical glass pressure vessel, which contains all of the components, such as actuators, ballast system, power supply, on-board computer and inertial sensor. Since the housing is spherically symmetric, the hydrodynamics of IAMBUS are uncoupled (e.g. a roll maneuver does not impact pitch or yaw). This hull shape enables IAMBUS to be used as a spacecraft attitude dynamics and control simulator with full rotational freedom. / Master of Science

The process developed herein uses a Multiple Objective Genetic Optimization (MOGO) algorithm. The optimization is implemented in ModelCenter (MC) from Phoenix Integration. It uses a genetic algorithm that searches the design space for optimal, feasible designs by considering three Measures of Performance (MOPs): Cost, Effectiveness, and Risk. The complete synthesis model is comprised of an input module, the three primary AUV synthesis modules, a constraint module, three objective modules, and a genetic algorithm. The effectiveness rating determined by the synthesis model is based on nine attributes identified in the US Navy's UUV Master Plan and four performance-based attributes calculated by the synthesis model. To solve multi-attribute decision problems the Analytical Hierarchy Process (AHP) is used. Once the MOGO has generated a final generation of optimal, feasible designs the decision-maker(s) can choose candidate designs for further analysis. A sample AUV Synthesis was performed and five candidate AUVs were analyzed. / Master of Science

Robust state estimation solutions must deal with faulty measurements, called outliers, and unknown data associations, which lead to multiple feasible hypotheses. Take, for instance, the scenario of tracking two indistinguishable targets based on position measurements, where each measurement could refer to either of the targets or even be a faulty reading. Common estimation methods model the state as having a unimodal distribution, so they are called unimodal methods. Likewise, multimodal methods model the state as a multimodal distribution. Difficult problems, such as autonomous underwater vehicle (AUV) navigation relying on acoustic localization, frequently involve recurring outliers. In these situations, the correct hypothesis only emerges as the most likely one when a substantial number of measurements are considered. Robust solutions for these problems need to consider multiple hypotheses simultaneously, which, in turn, calls for the representation of multimodal distributions. In this work, a novel approximate inference method is presented, called the Gaussian mixture sum-product algorithm (GM-SPA), as it implements the sum-product algorithm (SPA) for Gaussian mixtures. The GM-SPA can exactly represent under-constrained linear measurements and approximate important non-linear models, such as range measurements and 2D pose kinematics. The outlier robustness of the GM-SPA is tested and compared against the particle filter (PF) and multimodal incremental smoothing and mapping (MMiSAM), both of which are non-parametric methods. Robustness, accuracy, and run-time are improved in simulation tests. The test problems include 1D localization with unknown data association, 3D linear target tracking with correlated outliers, and 2D range-only pose estimation with Gaussian mixture noise. / Robusta lösningar för tillståndsuppskattning måste kunna hantera felaktiga mätningar, så kallade outliers, och okända dataassociationer, vilket leder till flera möjliga hypoteser. Ta till exempel scenariot att spåra två likadana mål baserat på positionsmätningar, där varje mätning kan tillhöra något av målen eller till och med vara en felaktig avläsning. Vanliga skattningsmetoder modellerar tillståndet som en unimodal fördelning, och kallas därför unimodala metoder. På samma sätt modellerar multimodala metoder tillståndet som en multimodal fördelning. Svåra problem, som navigering av autonoma undervattensfarkoster (AUV) med hjälp av akustisk lokalisering, involverar ofta upprepade outliers. I dessa situationer framstår den korrekta hypotesen som den mest sannolika först när ett stort antal mätningar beaktas. Robusta lösningar för dessa problem måste ta hänsyn till flera hypoteser samtidigt, vilket i sin tur kräver representation av multimodala fördelningar. I detta arbete presenteras en ny approximativ inferensmetod, kallad Gaussian mixture sum-product algorithm (GM-SPA), eftersom den implementerar sum-product algorithm (SPA) för gaussiska blandningar. GM-SPA kan representera underbegränsade linjära mätningar exakt och approximera viktiga icke-linjära modeller, till exempel avståndsmätningar eller 2D-posekinematik. GM-SPA:s robusthet mot outliers testas och jämförs med partikelfiltret (PF) och multimodal incremental smoothing and mapping (MM-iSAM), som båda är icke-parametriska metoder. Robusthet, noggrannhet och körtid förbättras i simuleringstester. Simulerade tester inkluderar 1D-lokalisering med okänd dataassociation, 3D linjär målföljning med korrelerade outliers och 2D-ställningsuppskattning av endast räckvidd med Gaussiskt blandningsljud. / Soluções robustas para estimação de estado devem lidar com medidas defeituosas, chamadas de outliers, e com associações de dados desconhecidas, que levam a múltiplas hipóteses possíveis. Considere-se, por exemplo, o cenário de rastreamento de dois alvos indistinguíveis com base em medidas de posição, em que cada medida pode-se referir a qualquer um dos alvos ou até mesmo ser uma leitura defeituosa. Métodos de estimação comuns modelam o estado como tendo uma distribuição unimodal, sendo assim chamados de métodos unimodais. Da mesma forma, métodos multimodais modelam o estado como uma distribuição multimodal. Problemas difíceis, como a navegação de veículos subaquáticos autónomos (AUVs) baseada em localização acústica, frequentemente envolvem outliers recorrentes. Nestas situações, a hipótese correta apenas surge como a mais provável quando um número substancial de medidas é considerado. Soluções robustas para estes problemas precisam de considerar múltiplas hipóteses simultaneamente, o que, por sua vez, exige a representação de distribuições multimodais. Neste trabalho, é apresentado um novo método de inferência aproximada, chamado Gaussian mixture sum-product algorithm (GM-SPA), pois implementa o sum-product algorithm (SPA) para misturas Gaussianas. O GM-SPA pode representar exatamente medidas lineares sub-determinadas e aproximar modelos não lineares importantes, como medidas de distância e cinemática de pose 2D. A robustez a outliers do GM-SPA é testada e comparada com o filtro de partículas (PF) e com multimodal incremental smoothing and mapping (MM- -iSAM), ambos métodos não-paramétricos. A robustez, a exatidão e o tempo de execução em testes de simulação são melhorados. Os problemas de teste incluem localização 1D com associação de dados desconhecida, rastreamento linear de alvos em 3D com outliers correlacionados e estimação de pose 2D com base em medidas de distância com ruído de mistura Gaussiana.